Evaluating academic motivation among Chinese secondary EFL learners: validation and measurement invariance

Abstract

Inspired by self-determination theory (SDT), the Academic Motivation Scale (AMS) was developed to measure students’ learning motivation. While the AMS has been widely validated and used in educational contexts, it has generally overlooked the domain-specific nature of academic motivation, particularly in learning English as a foreign language (EFL) in China, home to the world’s largest population of EFL learners. This study sought to adapt the AMS and substantiate its validity using both within-network and between-network approaches with a sample of 1,390 Chinese secondary EFL learners. Results from item analysis, internal consistency, and confirmatory factor analysis (CFA) showed that the 28-item EFL-specific AMS exhibits robust psychometric properties, characterised by a seven-factor structure, and demonstrates invariance across gender and grade levels. Structural equation modelling (SEM) analyses further indicated that both extrinsic and intrinsic motivations are positively correlated with perceived teacher support, engagement, and achievement, whereas amotivation is inversely associated with these outcomes. Implications, limitations, and directions for future research are also discussed.

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Kang et al. BMC Psychology (2025) 13:235
https://doi.org/10.1186/s40359-025-02573-8
academic motivation has emerged as a prominent focus
within educational psychology, with extensive explora-
tion of its antecedents—such as teachers’ interpersonal
involvement, social support, and psychological needs—
and its consequences, including academic achievement,
learning engagement, and positive self-concept [4–9].
Given the pivotal role of academic motivation in facilitat-
ing educational advancement, educators and researchers
have dedicated eective methods for enhancing students’
academic motivation [10, 11]. However, there remains
a lack of consensus regarding the denitions and con-
structs used to assess academic motivation. For example,
Deci and Ryan used an intrinsic motivation construct to
portray academic motivation [12], while Ryan and Deci
expanded this framework by incorporating both intrinsic
and extrinsic motivation [13]. In contrast, Vallerand et al.
Introduction
Motivation is one of the most critical factors inuenc-
ing students’ learning outcomes in English as a foreign
language (EFL) [1, 2]. Self-determination theory (SDT)
conceptualizes academic motivation as an individual’s
perception of the personal value, enjoyment, and satisfac-
tion of academic pursuits [3]. Over the past four decades,
BMC Psychology
*Correspondence:
Dongpin Hu
dhu@eduhk.hk
1School of Mathematics and Information Science, Guangzhou University,
Guangzhou, China
2Department of Curriculum and Instruction, Faculty of Education and
Human Development, The Education University of Hong Kong, Hong
Kong, China
3School of Humanities and Education, Foshan University, Foshan, China
4Faculty of Education, Shenzhen University, Shenzhen, China
Abstract
Inspired by self-determination theory (SDT), the Academic Motivation Scale (AMS) was developed to measure
students’ learning motivation. While the AMS has been widely validated and used in educational contexts, it has
generally overlooked the domain-specic nature of academic motivation, particularly in learning English as a
foreign language (EFL) in China, home to the world’s largest population of EFL learners. This study sought to adapt
the AMS and substantiate its validity using both within-network and between-network approaches with a sample
of 1,390 Chinese secondary EFL learners. Results from item analysis, internal consistency, and conrmatory factor
analysis (CFA) showed that the 28-item EFL-specic AMS exhibits robust psychometric properties, characterised
by a seven-factor structure, and demonstrates invariance across gender and grade levels. Structural equation
modelling (SEM) analyses further indicated that both extrinsic and intrinsic motivations are positively correlated
with perceived teacher support, engagement, and achievement, whereas amotivation is inversely associated with
these outcomes. Implications, limitations, and directions for future research are also discussed.
Keywords Academic motivation scale, Validation, Measurement invariance, Self-determination theory, Chinese
secondary EFL learners
Evaluating academic motivation among
Chinese secondary EFL learners: validation
and measurement invariance
XiaKang1, DongpinHu2*, YajunWu3 and JiutongLuo4
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Kang et al. BMC Psychology (2025) 13:235
proposed a self-determination continuum of academic
motivation [14], encompassing amotivation, extrinsic
motivation, and intrinsic motivation.
Based on the SDT, the academic motivation scale
(AMS) oers a comprehensive framework for evaluating
academic motivation by encompassing the dimensions
of amotivation, intrinsic, and extrinsic motivation. is
multidimensional approach enables a nuanced assess-
ment of students’ academic motivation from various per-
spectives [15]. Despite the widespread use of the AMS
among scholars [14–19], there remains a lack of consen-
sus concerning its dimensionality and structural compo-
sition. For example, based on factor analysis, researchers
have proposed various structural models for the AMS,
resulting in three-factor [16], four-factor [17], ve-fac-
tor [18], and seven-factor congurations [14, 15]. What
structural characteristics does the AMS exhibit among
Chinese secondary EFL learners? Aside from Zhang et
al. [20], who investigated the validity of the AMS among
Chinese high school and vocational high school students,
there is a notable absence of research that considers the
domain specicity of the AMS and examines the struc-
tural characteristics and validity of the EFL-related AMS.
In addition to neglecting the domain specicity of the
AMS [15, 19], existing studies have seldom addressed
the measurement invariance of the AMS across dierent
genders and grade levels. For instance, both [21] and [22]
observed that female students exhibited higher levels of
academic motivation than their male counterparts, high-
lighting signicant gender dierences in academic moti-
vation. In a study focused on sixth and seventh-grade
middle school students in the United States [23], it was
found that the motivation levels of seventh-grade stu-
dents were signicantly lower than those of their sixth-
grade counterparts. is nding suggests the presence of
grade-specic variations in academic motivation. ere-
fore, while assessing the validity of the AMS, it is essen-
tial to analyse measurement invariance across genders
and grade levels to broaden the applicability of this scale
further.
To address the shortcomings identied in the current
literature, the present study seeks to investigate the fac-
torial structure and applicability of the AMS within the
context of EFL in mainland China. Additionally, this
study aims to assess the measurement invariance of the
AMS across dierent genders and grade levels. Speci-
cally, following Martin’s construct validation framework
[24], the within-network approach involved item-level
analysis, factor correlation matrix inspection, conrma-
tory factor analysis (CFA), and invariance assessment
across gender and grade levels were conducted. e
between-network approach was also employed to investi-
gate associations between the AMS and the theoretically
relevant constructs, including academic engagement,
teacher support, and academic achievement. is
research is poised to elucidate the concept, components,
and structure of the AMS and develop a reliable tool for
assessing the academic motivation proles of Chinese
EFL learners.
Literature review
To evaluate the between-network validity of the AMS for
Chinese secondary EFL learners, we examined the zero-
order correlations between the EFL AMS and a range
of related constructs, including academic engagement,
teacher support, and academic achievement. Further-
more, we analysed the predictive eects of EFL AMS on
these constructs. Academic engagement is considered
an external manifestation of academic motivation [25]
and demonstrates a signicant correlation with it [26].
Additionally, the substantial correlation between aca-
demic motivation and academic achievement [27], as
well as between academic motivation and teacher sup-
port [28], suggests that both academic achievement and
teacher support may also serve as suitable metrics for
evaluating the between-network validity of the AMS. In
summary, academic engagement, teacher support, and
academic achievement are the key metrics for assessing
the between-network validity of the AMS.
Academic motivation
Traditionally, academic motivation was described as the
psychological factors that drive individuals to engage in
academic activities [15, 29]. Self-determination theory
(SDT) is one of the most impactful theoretical models for
understanding motivation and has been widely applied
in EFL studies as a valuable analytical framework [30,
31]. According to the SDT, academic motivation could
be divided into three forms amotivation, extrinsic moti-
vation, and intrinsic motivation in terms of the levels of
self-determination [13]. Amotivation, the lowest level
of self-determination, refers to the lack of motivation or
the absence of perceiving any reasons to engage in learn-
ing activities [13]. As expected, amotivation harms many
academic outcomes, such as poor academic performance,
low self-esteem, behavioural problems, absenteeism, and
school dropout [32, 33].
Intrinsic motivation, the most autonomous type,
denotes individuals’ engagement in learning activi-
ties driven by inherent satisfaction and enjoyment [13].
Highly intrinsically motivated students are likely to
achieve various favourable outcomes, including height-
ened engagement, elevated self-ecacy and ow experi-
ence, and enhanced academic performance [34]. Within
the spectrum of self-determined motivation, intrinsic
motivation can be further categorised into three dimen-
sions: intrinsic motivation-to know (IM-TK), intrinsic
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Kang et al. BMC Psychology (2025) 13:235
motivation-to accomplish (IM-TA), and intrinsic motiva-
tion-to experience stimulation (IM-ES) [14].
Extrinsic motivation exists on the continuum between
amotivation and intrinsic motivation, which refers to
the drive or incentive to engage in learning activities or
pursue academic goals that are externally driven, such
as obtaining rewards or avoiding punishments [13].
Research has identied several benets associated with
extrinsic motivation, including enhancing academic con-
dence, the development of internal attributions, and
promoting intrinsic motivation [35]. Based on the degree
of autonomy, extrinsic motivation can be further sub-
divided into three types: extrinsic motivation-external
regulation (EM-ER), extrinsic motivation-introjected
regulation (EM-IN), and extrinsic motivation-identied
regulation (EM-ID) [14].
e domain specicity and group dierences in aca-
demic motivation indicate that the validity of the AMS
in specic academic domains and among specic groups
requires further exploration. Green et al. documented
distinctive patterns of academic motivation across sub-
jects [36], such as English, mathematics, and science, in
a study with Australian high school students. Similarly,
Lepper et al. found that American students’ intrinsic
motivation declined signicantly from primary to sec-
ondary education [37]. However, studies on the construct
validity of AMS within specic non-Western populations
remain limited [15]. Aside from [18], which established
factorial invariance of the AMS across genders, few stud-
ies have investigated the eects of gender and grade level
on this scale. erefore, a validation study on the AMS
focusing on Chinese secondary school students’ EFL
learning and validating the factorial invariance of the
scale across gender and grade levels would signicantly
enhance the understanding of motivation within the eld
of EFL education.
Academic engagement
Academic engagement refers to the extent to which stu-
dents invest physical and mental energy in their learning
activities [38]. As the manifestation of motivation, aca-
demic engagement reects a student’s level of academic
motivation [26]. Also, academic motivation could reect
a student’s subsequent learning behaviours and devel-
opment [39]. Fredricks et al. explored the multifaceted
nature of this construct and identied that academic
engagement consists of three sub-facets: behavioural
engagement (e.g., involvement in in-class and extracur-
ricular activities), emotional engagement (e.g., emotional
investment towards learning activities), and cognitive
engagement (e.g., use of self-regulated learning strate-
gies) [38]. In addition, Reeve and Tseng documented that
apart from behavioural, emotional, and cognitive engage-
ment, agentic engagement, which refers to a student’s
dynamic construction of learning messages, is the fourth
aspect of academic engagement [40].
is study focused on the most crucial aspect of aca-
demic engagement, namely, behavioural engagement
[41]. On the one hand, the impact of emotional and cog-
nitive engagement on educational outcomes works indi-
rectly via behavioural engagement [42]. On the other
hand, behavioural engagement has a more substantial
impact on school outcomes than the other aspects of
academic engagement [43]. As the core aspect of aca-
demic engagement, behavioural engagement signicantly
predicts academic motivation [44], academic achieve-
ment [45], self-regulation [46], and subjective well-being
[47]. Also, empirical studies identied the precursors
of behavioural engagement, including social support,
teacher-student relationship quality, achievement emo-
tions, academic motivation, and school psychological
capital [48, 49]. To add to the body of knowledge on the
antecedents of behavioural engagement in an EFL envi-
ronment, one goal of the present study was to examine
the predictive eect of academic motivation on behav-
ioural engagement.
Teacher support
Teacher support is generally dened as students’ per-
ceived care, concern, understanding of their needs, and
assistance in achieving educational goals [50]. Teachers
serve as an essential source of support for adolescents
during their learning and school-related activities, with
their inuence often surpassing that of parents [51].
For example, Zhao and Yang found that teacher sup-
port could directly impact learning engagement or exert
its inuence indirectly through mediators such as aca-
demic enjoyment and boredom in the context of Chi-
nese EFL education [52]. In a distinct study involving
Chinese college students majoring in English, the results
demonstrated that teacher support—an integral compo-
nent of social support—signicantly alleviates students’
emotional experiences of anxiety within the classroom
environment [53]. Furthermore, studies such as [54] and
[55] demonstrate that teacher support signicantly fos-
ters stronger motivational beliefs. Additionally, research
by Pekrun et al. indicates that teacher support mediates
the relationship between achievement goals (especially
academic motivation) and academic achievement, indi-
cating that academic motivation plays a predictive role
in teacher support [56]. Consequently, it is crucial to
explore further the dynamic interaction between aca-
demic motivation and teacher support, especially in EFL
education, where teacher support may uniquely shape
students’ language learning motivation and outcomes.
erefore, more empirical studies are warranted to exam-
ine these connections in greater depth, providing valu-
able insights for both research and educational practice.
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Kang et al. BMC Psychology (2025) 13:235
Academic achievement
As a core indicator of educational outcomes, academic
achievement represents the level of knowledge attained
by students and is of paramount importance to both
teachers and students at all educational stages [57]. For
students, achieving excellent academic achievement is
a marker of academic honour and a gateway to higher
education, broader academic success, and the develop-
ment of valuable human capital [58]. In the Chinese con-
text, academic achievement carries additional cultural
weight, deeply rooted in traditional values that prioritise
education as a crucial pathway to personal and societal
advancement [59]. e pressure to excel, particularly in
key examination subjects such as Chinese, mathematics,
and English, is intensied by these scores’ critical role in
university admissions and broader socio-economic pros-
pects [60].
Considering the signicance of academic achievement,
empirical research has identied a number of precur-
sors of academic achievement, such as academic moti-
vation, learning engagement, achievement emotions,
and teacher support [6, 8, 52, 56]. Given the paucity of
research on the domain specicity of academic motiva-
tion in an EFL context, this study examines the relation-
ship between EFL-related academic motivation and EFL
achievement among Chinese secondary EFL learners.
Linking academic motivation to engagement, teacher
support, and achievement
Previous research has demonstrated the predictive
eects of academic motivation on learning engagement
[26, 61], teacher support [56], and academic achievement
[8, 32], providing empirical evidence of the correlations
between these variables. While other potential anteced-
ents of academic outcomes, such as psychological needs
[62]and self-concept [63], are also well-established in
the literature, this study specically focuses on academic
motivation due to its central role in driving students’
active engagement with learning, fostering teacher-
student relationships, and enhancing performance. e
strong connection between motivation and these educa-
tional outcomes makes it a key target for interventions to
improve student success, particularly in the EFL context.
Moreover, despite the robust evidence support-
ing the relationship between academic motivation and
these variables, much of the existing research has not
accounted for the domain specicity of academic moti-
vation, which suggests that further exploration of these
relationships is necessary. erefore, this study explored
the link between EFL-related academic motivation and
behavioural engagement, perceived teacher support, and
EFL achievement to better understand the predictive
eects of EFL-related academic motivation and establish
the EFL-related AMS’s between-network validity.
Rationale and research hypotheses
e present study seeks to address existing research
deciencies through three distinct yet interrelated
approaches. First, we employed a within-network meth-
odology to adapt the AMS for the EFL context, assess-
ing its factorial structure and construct validity among
Chinese secondary EFL learners. Second, we conducted
multi-group SEM to evaluate the measurement invari-
ance of the EFL-related AMS across dierent genders
and grade levels. ird, utilising a between-network
approach, we investigated the associations between EFL-
related academic motivation and perceived teacher sup-
port, academic motivation, and academic achievement,
thereby assessing the external validity of the adapted
EFL-related AMS. In summary, the present study aims to
address the following three research questions.
RQ1: What are the factorial structure and psychometric
properties of EFL-related AMS among Chinese second-
ary EFL learners?
RQ2: Does the EFL-related AMS exhibit measurement
invariance across gender identity and grade levels?
RQ3: Does the EFL-related AMS demonstrate strong
external validity as assessed through a between-network
approach?
Methodology
Participants and procedures
e questionnaire survey included 1,390 secondary EFL
learners from Kunming City, Yunnan Province, China.
Among these participants, 639 were males (46.0%) and
751 were females (51.0%). e mean age of the partici-
pants was 13.46 years old (SD = 0.74), with ages ranging
from 12 to 17 years. e participants were in seventh and
eighth grades, with nearly equivalent group sizes: 697
seventh and 693 eighth graders.
e sampling procedure comprised three key aspects.
First, a stratied three-stage sampling method was
employed to select participants. Secondary schools in
Kunming City were classied into three levels based on
ocial accreditation. Convenient sampling was then
applied to select one school from each level, designated
as schools A, B, and C in descending order of accredita-
tion. Subsequently, half of the seventh and eighth grades
from these three schools were randomly selected, result-
ing in a total of 30 classes participating in the question-
naire survey (School A: 14 classes, N = 662, 47.9%; School
B: 7 classes, N = 335, 24.0%; School C: 9 classes, N = 393,
28.1%). Second, the survey was administered in Chinese.
e original AMS, written in English, was rst trans-
lated into Chinese and then back-translated into English
by two bilingual researchers to ensure the face validity
of the measurement scale (see Appendix). ird, ethical
approval for the present study was obtained from the rst
author’s university (Human Research Ethics Committee’s
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Kang et al. BMC Psychology (2025) 13:235
Reference Number: EA2003020) in Hong Kong. Prior to
the commencement of the questionnaire survey, all par-
ticipants signed consent forms, verbal informed consent
was also obtained from participants’ parents or legal
guardians, and anonymous pen-and-paper question-
naires were then distributed.
Instruments
EFL-related academic motivation scale (EFL-related AMS)
e 28-item AMS initially developed by Vallerand et al.
[64] measured the EFL-related academic motivation.
Considering the specic nature of academic motivation
[19], all items of the original AMS were reformulated
to t the EFL learning context better. e EFL-related
AMS includes three aspects of amotivation, intrinsic,
and extrinsic motivation, encompassing seven specic
subscales. For example, one item of the amotivation sub-
scale was rephrased from “Honestly, I don’t know; I really
feel that I am wasting my time in school” to “I feel that
learning English is a waste of time”. Example items of the
other six subscales were “e more English knowledge I
master, the happier I become” (4-item IM-TK), “I learn
English for the pleasure I experience while surpassing
myself” (4-item IM-TA), “For me, learning English is fun”
(4-item IM-ES), “Learning English is to nd a good job”
(4-item EM-ER), “Learning English is to have an addi-
tional option when looking for a job in the future”(4-item
EM-ID), and “Learning English is to prove to others that
I am an intelligent person” (4-item EM-IN). Participants
responded to the 28 items in the seven sub-scales of the
EFL-related AMS by applying a 5-point Likert scale rang-
ing from “1 (Strongly disagree)” to “5 (Strongly agree)”.
Higher scores indicate greater agreement with the corre-
sponding item.
Foreign language learning engagement scale
e 4-item behavioural engagement scale adapted from
the Engagement vs. Dissatisfaction with Learning Ques-
tionnaire [65] was utilised to measure participants’
foreign language learning engagement. Participants
responded to the items on a ve-point Likert scale, with
higher scores indicating a higher commitment to English
learning. e reliability of this scale has been validated
in previous studies [43, 48]. e CFA results indicated
that the model t the data well: χ2(2) = 9.650, p <.001,
CFI = 0.997, TLI = 0.992, R MSEA = 0.052, 90% CI [0.023,
0.088], SRMR = 0.007, indicating that foreign language
learning engagement scale possesses strong construct
validity. Additionally, this scale demonstrated high inter-
nal consistency, with Cronbach’s α of 0.89. Furthermore,
foreign language learning engagement was modelled as a
latent variable in the SEM analysis.
Perceived teacher support scale
e participants’ perceived support from their English
teachers was measured by a ve-item scale adapted from
the Child and Adolescent Social Support Scale [66]. One
example item is “My English teacher takes care of my
feelings”. Participants rated their agreement with the ve
statements on a ve-point Likert scale. is scale has
demonstrated good validity and internal consistency in
prior research [52, 54, 67]. e perceived teacher support
scale exhibited good internal consistency, with a Cron-
bach’s α of 0.86. e CFA results showed that the model
t the data well: χ2(5) = 31.007, p <.001, CFI = 0.991,
TLI = 0.982, RMSEA = 0.061, 90% CI [0.042, 0.083],
SRMR = 0.017. ese ndings suggest that the perceived
teacher support scale possesses good construct validity.
e SEM analysis treated perceived teacher support as a
latent variable.
EFL achievement
Participants’ English scores from their nal examination
were collected to characterise their EFL achievement.
e face validity of the examination paper is ensured, as it
was uniformly formulated by the local education bureau.
e examination is scored out of 100 points, with higher
scores indicative of more outstanding EFL achievement.
In the SEM analysis, EFL achievement was treated as an
observed variable.
Data analysis
We utilised SPSS 23.0 and Mplus 8.3 to analyse the data
in several stages [68]. Initially, relevant assumptions asso-
ciated with multivariate statistical analyses were assessed
to detect any outliers before conducting pertinent statis-
tical analyses. Following this, we focused on the validity
of the within-network construct, starting with a detailed
item and reliability analysis. en, dierent CFA mod-
els were tested to determine the best t for the data.
We compared the seven-factor model (Model 1) with
four alternative models to explore the most suitable t.
More specically, one of the alternatives (Model 2) is a
ve-factor model, which lumps all intrinsic motivation
items into one dimension and keeps amotivation and the
three ordered extrinsic motivation factors distinct from
each other [18]. Another alternative (Model 3), proposed
by [16], is a three-factor model similar to Model 2, but
with the extrinsic motivation items combined into one
dimension. Meanwhile, Model 4 is a one-factor model
that combines all items into an omnibus motivation fac-
tor, and Model 5 is a hierarchical model with two sec-
ond-order factors and one rst factor (i.e., amotion). e
two second-order factors in Model 5 are general extrin-
sic motivation, underpinned by the rst-order factors of
EM-ID, EM-IN, and EM-ER, and intrinsic motivation,
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Kang et al. BMC Psychology (2025) 13:235
which is underpinned by the rst-order factors of IM-TK,
IM-TA, and IM-ES.
To assess the model t, we considered multiple indi-
ces and compared the goodness-of-t of the ve factorial
models. Indexes of chi-square to the degree of freedom
ratio (χ2/df), comparative t index (CFI), Tucker-Lewis
index (TLI), root mean square error of approximation
(RMSEA), and standardised root mean square residual
(SRMR) were adopted to evaluate models’ goodness-of-
t. More specically, a model ts well with the data if
the values of RM SEA ≤ 0.06, SRMR ≤ 0.08, C FI ≥ 0.90 and
TLI ≥ 0.90 [69]. Furthermore, multi-group CFA was con-
ducted to examine the measurement invariance of the
identied measurement model across gender and grade
levels. In this phase, we followed the approach proposed
by [70] to sequentially test the measurement model’s con-
gural, metric, and scalar invariance across gender and
grade levels. When two nested models vary in the com-
parative t index (ΔCFI) of less than 0.01 [71], and the
overall model t is deemed adequate [72], measurement
invariance is established.
Besides, the between-network validity of the EFL-
related academic motivation was assessed in two steps.
First, zero-order correlations were tested between EFL-
related motivation and perceived teacher support, learn-
ing engagement, and EFL achievement. Second, SEM
analyses were conducted to validate the predictive eects
of EFL-related motivation on perceived teacher support,
learning engagement, and EFL achievement while con-
trolling for gender, age, and grade level.
Results
Preliminary analysis
Following the recommendations of [73], relevant assump-
tions associated with multivariate statistical analyses
were evaluated before conducting the pertinent statisti-
cal analyses. Based on the Q-Q plots of each EFL-related
motivation indicator variable, which showed a generally
linear pattern, indicating that data approximately follow a
normal distribution. To eliminate the inuence of outliers
on the correlation between studied variables, the criteria
that the largest-magnitude z-score beyond ± 3 would be
considered as univariate outliers were adopted [74], and
it was found that there were no outliers. Besides, using a
threshold of 4 for Mahalanobis values, 5 cases were iden-
tied as outliers and excluded from the data.
Within-network construct validity of EFL-related
motivation
Item level analysis
Item analysis was rst conducted to detect the discrimi-
nation and eectiveness of all items in the EFL-related
AMS. Specically, 27% of the highest and lowest scores
were selected and analysed in this phase [75]. Our analy-
sis revealed that for each item, the mean values of high
and low groups were signicantly dierent at a 0.001
level, indicating that all items of EFL-related AMS were
discriminative and eective. erefore, all items could be
used in the formal investigation. en, item-total corre-
lation analyses were conducted to detect the correlation
between each item for each global subscale. According to
the benchmark (r =.30) proposed by Pallant [76], all items
in the EFL-related AMS had good homogeneity (ranging
from 0.45 to 0.80), indicating that no items need to be
eliminated.
Conrmatory factor analysis
e CFA results for ve proposed EFL-related AMS
models are presented in Table1. Both Model 3 and Model
4 showed CFI and TLI values below 0.90, indicating inad-
equate t to the data. Regarding the RMSEA and SRMR
values, Model 2 demonstrated an RMSEA value exceed-
ing 0.60, and both Model 2 and Model 5 had SRMR val-
ues greater than 0.08, further indicating that these two
models did not t the data well. In contrast, Model 1 in
the CFA demonstrated a satisfactory t to the data, indi-
cating that the 28-item seven-factor model appropriately
represents the observed data.
In addition, this study utilised a chi-square dierence
test to determine if the alternative models (Models 2–5)
signicantly improved data t over the seven-factor
model (Model 1). e test results revealed that Model 1
had a superior t to the data compared to all four alter-
native models. Second only to Model 1, Model 2 appears
to be plausible for CFI/TLI values exceeded 0.90, RMSEA
value slightly exceeded 0.06, and SRMR value was less
than 0.08. Model 2 aligns with the model proposed by
[3, 13], in which the three subscales of intrinsic motiva-
tion were merged into a single scale. Despite not being
Table 1 Goodness-of-t indices for the seven-factor model and alternative models
Model χ2df χ2/df CFI TLI RMSEA 90% C.I. SRMR Δχ2Δχ2/df
M1 Seven-factor 1790.199*** 329 5.441 0.931 0.920 0.057 0.054, 0.059 0.069 - -
M2 Five-factor 2204.210*** 340 6.483 0.911 0.902 0.063 0.060, 0.065 0.072 414.011*** 11
M3 Three-factor 4321.917*** 347 12.455 0.811 0.794 0.091 0.088, 0.093 0.114 2531.718*** 18
M4 One-factor 7128.246*** 350 20.366 0.678 0.652 0.118 0.116, 0.121 0.119 5338.047*** 21
M5 Hierarchical 2326.299*** 341 6.822 0.906 0.896 0.065 0.062, 0.067 0.092 536.100*** 12
Note: *** p < .001
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Kang et al. BMC Psychology (2025) 13:235
optimal, Model 2 suggests that the distinctions among
the three dimensions of intrinsic motivation are weaker
than those among the three dimensions of extrinsic moti-
vation [15].
Apart from having satisfactory t indices, all the stan-
dardised factor loadings for each item in the seven-factor
model (Model 1) were signicant at p <.001. ese load-
ings ranged from 0.55 to 0.86 (see Fig.1) and surpassed
the recommended threshold value of 0.40 [77]. As a
result, the seven-factor model of the EFL-related AMS t
the data best and thus was adopted.
After determining the seven-factor model of the EFL-
related AMS, we examined the model t of each of the
seven subscales. Table 2 presents the goodness-of-t
indices for the seven subscales of the EFL-related AMS.
e CFI and TLI values were higher than the cuto of
0.90, and the values of RMSEA and SRMR were less than
the threshold values of 0.06 and 0.08, respectively. at
is, all the seven subscales tted the data well.
Reliability
e internal consistency reliability of the seven subscales
of the EFL-related AMS was evaluated using Cronbach’s
alpha. According to the cuto for an acceptable alpha
value (Cronbach’s α ≥ 0.70) proposed by [78], all the seven
subscales had good internal consistency: Cronbach’s
α = 0.77 for amotivation, Cronbach’s α = 0.80 for EM-ER,
Cronbach’s α = 0.77 for EM-ID, Cronbach’s α = 0.81 for
EM-IN, Cronbach’s α = 0.85 for IM-TK, Cronbach’s
α = 0.87 for IM-TA, and Cronbach’s α = 0.89 for IM-ES
(see Table3).
Furthermore, the internal consistency reliability of the
seven subscales of the EFL-related AMS was re-estimated
by conducting item deletion. Specically, we calculated
the Cronbach’s alpha of one subscale (e.g., amotivation
subscale) when one item of this scale was deleted (e.g., “I
feel that learning English is a waste of time.”). Systemati-
cally and sequentially, one item was removed each time,
and it was found that the Cronbach’s alpha coecient
for the seven subscales of the EFL-related AMS would
slightly decrease. us, it could be concluded that each
item within these seven subscales satises the benchmark
and should not be deleted.
Table 2 Goodness-of-t indices for the seven-factor model
Model χ2df CFI TLI RMSEA 90% C.I. SRMR
Amotivation 343.857 105 0.973 0.966 0.040 0.036, 0.045 0.037
IM-To Know 305.099 105 0.981 0.975 0.037 0.032,0.042 0.037
IM-To accomplish 252.684 105 0.986 0.982 0.032 0.027, 0.037 0.034
IM-Stimulation 337.816 105 0.979 0.974 0.040 0.035, 0.045 0.041
EM-Identied 338.962 105 0.974 0.967 0.040 0.035, 0.045 0.037
EM-Introjected 275.174 105 0.980 0.975 0.034 0.029, 0.039 0.031
EM-External 528.845 105 0.954 0.941 0.054 0.049, 0.058 0.066
Fig. 1 Graphical representation of the seven-factor model and factor loadings
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Page 8 of 13
Kang et al. BMC Psychology (2025) 13:235
Measurement invariance across gender and grade levels
Following identifying the better-t model, multi-group
CFA was conducted to ascertain the measurement
invariance of the seven-factor model of EFL-related AMS
across gender and grade levels. Following the sequential
framework established by [70], congural, metric, and
scalar invariance of the EFL-related AMS were system-
atically tested stepwise to ensure a comprehensive under-
standing of its measurement properties across diverse
groups.
Measurement invariance across gender. To evalu-
ate the measurement invariance of the seven-factor
model of EFL-related AMS between male and female
groups, initially, we began by examining separate baseline
models. e data t the model well for the male group:
RMSEA = 0.061, 90% C.I. = (0.057, 0.065), CFI = 0.921,
TLI = 0.910, and SRMR = 0.066. Likewise, the female
group’s data also demonstrated a good model t, show-
ing RMSEA = 0.058, 90% C.I. = (0.055, 0.062), CFI = 0.924,
TLI = 0.912, and SRMR = 0.075. ese results suggest
that the seven-factor model of EFL-related AMS seemed
cross-validated across both male and female groups. Sub-
sequently, tests of overall congural, metric, and scalar
invariance of the seven-factor model of EFL-related AMS
across genders were conducted. As presented in Table4,
the overall model ts were good, with the value of ΔCFIs
between two nested models being 0.004 or more minor.
is nding meets the cuto criteria proposed by [71],
thereby conrming the establishment of congural, met-
ric and scalar invariance across genders.
Measurement invariance across grade levels. Base-
line model measurement invariance of the seven-factor
model of EFL-related AMS was also evaluated across
seventh-graders and eighth-graders. For seventh-grad-
ers, the data tted the model well: RMSEA = 0.056,
90% CI = (0.052, 0.060), CFI = 0.931, TLI = 0.920, and
SRMR = 0.070. e baseline model also tted the data of
eighth-graders: RMSEA = 0.064, 90% CI = (0.060, 0.067),
CFI = 0.917, TLI = 0.904, and SRMR = 0.074. en, cong-
ural, metric, and scalar invariance were tested stepwise.
As shown in Table2, the overall model ts were good,
and the value of ΔCFIs between two nested models was
equal to 0.002 or smaller, suggesting that congural, met-
ric and scalar invariance were established across the pop-
ulations of seventh graders and eighth graders.
Between-network validation
e seven-factor model of EFL-related AMS possessed
robust psychometric properties and maintained mea-
surement invariance across genders and grade levels
when measuring the academic motivation of Chinese
EFL learners. Additionally, to evaluate the between-net-
work validity of the seven-factor model, correlations were
examined between EFL-related academic motivation and
Table 3 Results of descriptive statistics, internal reliabilities, and bivariate correlations
1 2 3 4 5 6 7 8 9 10 11 12 13
1. AMO -
2. IM-TK − 0.521** -
3. IM-TA − 0.492** 0.807** -
4. IM-ES − 0.522** 0.810** 0.770** -
5. EM-ID − 0.396** 0.617** 0.584** 0.479** -
6. EM-IN − 0.034 0.270** 0.310** 0.250** 0.325** -
7. EM-ER 0.023 0.135** 0.143** 0.066*0.445** 0.477** -
8. EG − 0.491** 0.661** 0.647** 0.683** 0.471** 0.221** 0.103** -
9. PTS − 0.454** 0.576** 0.546** 0.574** 0.496** 0.170** 0.124** 0.593** -
10. EFLA − 0.373** 0.351** 0.350** 0.373** 0.267** 0.096** 0.028 0.405** 0.339** -
11. Gender − 0.204** 0.166** 0.131** 0.155** 0.127** 0.026 − 0.009 0.130** 0.084** 0.165** -
12. Age 0.124** − 0.028 − 0.053*− 0.066*− 0.026 − 0.033 − 0.033 − 0.029 − 0.040 − 0.036 − 0.086** -
13. Grade level 0.122** − 0.020 − 0.019 − 0.064*− 0.022 − 0.010 − 0.027 − 0.032 − 0.049 0.010 − 0.025 0.665** -
Mean 2.133 3.533 3.477 3.369 3.920 2.819 3.121 3.493 3.788 67.810 - - -
SD 0.835 0.817 0.825 0.844 0.731 0.855 0.863 0.792 0.730 21.071 - - -
Cronbach’s alpha 0.77 0.85 0.87 0.89 0.77 0.81 0.80 0.89 0.86 - - - -
Notes: AMO = Amotivation; EG = Foreign Lang uage Learning Engagem ent; PTS = Perceiv ed Teacher Supp ort; EFLA = EFL Achi evement
** p <.01; * p <.05
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Page 9 of 13
Kang et al. BMC Psychology (2025) 13:235
academic and well-being outcomes, including learn-
ing engagement, perceived teacher support, and EFL
achievement.
Bivariate correlations
Table 3 showcases the descriptive statistics, internal
reliabilities of the studied variables, and bivariate cor-
relations among the variables. Consistent with expecta-
tions, amotivation exhibited negative correlations with
learning engagement, perceived teacher support, and
EFL achievement. Conversely, the three components of
intrinsic motivation (i.e., IM-TK, IM-TA, and IM-ES) and
the three elements of extrinsic motivation (i.e., EM-ER,
EM-ID, and EM-IN) displayed a positive correlation with
learning engagement, perceived teacher support, and
EFL achievement. In addition, gender, age, and grade lev-
els were observed to have signicant correlations with
the three components of EFL learning motivation and
the outcome variables of learning engagement, perceived
teacher support, and EFL achievement. is highlights
the importance of controlling for these three variables
when examining the correlations among the variables
under study.
Contributions of the seven motivational components to
academic engagement, perceived teacher support, and EFL
achievement
SEM was conducted to explore the predictive eects of
the seven motivational components on learning engage-
ment, perceived teacher support, and EFL achievement
while controlling for gender, age, and grade levels. As
shown in Table5, amotivation in learning English nega-
tively and strongly predicted learning engagement (β =
− 0.601, p <.001), perceived teacher support (β = − 0.556,
p <.001), and EFL achievement (β = − 0.417, p <.001).
Except for the insignicant prediction eects of extrin-
sic motivation-external regulation on EFL achievement,
the two other components of extrinsic motivation (i.e.,
EM-ID and EM-IN) and all three components of intrinsic
motivation (i.e., IM-TK, IM-TA, and IM-ES), are signi-
cantly and positively correlated with learning engage-
ment, perceived teacher support, and EFL achievement.
Discussion
In the current study, the quality of each item was rst
evaluated through item analysis, assessing the accuracy
and reliability of the items within their respective sub-
scales. By comparing the t of ve models of EFL-related
AMS, it was determined that the seven-factor measure-
ment model provided the best t to the data. Subse-
quently, measurement invariance of the seven-factor
measurement model was examined across gender and
grade levels. Additionally, the between-network valid-
ity of the EFL-related AMS was investigated by explor-
ing the predictive eects of EFL-related motivation on
learning engagement, perceived teacher support, and
EFL achievement within the context of Chinese second-
ary EFL learning. ese ndings contribute to the exist-
ing literature on the validity of the AMS, emphasising its
applicability to Chinese secondary EFL learners.
e item level analysis and conrmatory factor analy-
sis results revealed that the seven-factor model of EFL-
related AMS exhibited robust psychometric properties,
addressing the rst research question. Furthermore, we
measured the goodness-of-t indices for the seven sub-
scales of the EFL-related AMS, and each subscale dem-
onstrated a good t to the data, further validating the
appropriateness of the seven-factor measurement model.
is nding dovetails with previous studies on the mea-
surement model and related psychometric properties of
AMS [15, 79]. However, much of the existing research
has mainly focused on general school contexts within
Western settings (e.g., Hungary), neglecting the domain
specicity of academic motivation. e present study
addresses this gap by expanding the applicability of the
AMS and by adapting and validating the most suitable
model of the EFL-related AMS among Chinese second-
ary EFL learners. is contribution enriches the literature
and provides a more nuanced understanding of academic
motivation in the specic context of EFL learning for
Chinese students.
Results of multi-group CFA demonstrated robust
measurement invariance of the EFL-related AMS across
gender and grade levels; thereby, the second research
question was answered. ese ndings contribute to
and extend existing literature. For example, Caleon et al.
Table 4 Fit indices for measurement invariance tests of the model across gender and grade levels
Model χ2df CFI ΔCFI TLI RMSEA 90% C.I. SRMR
M1a: Congural invariance 2275.89 658 0.922 - 0.911 0.059 0.057, 0.062 0.071
M2a: Metric invariance 2319.201 679 0.921 0.001 0.912 0.059 0.056,0.062 0.073
M3a: Scalar invariance 2445.959 707 0.917 0.004 0.911 0.059 0.057, 0.062 0.080
M4b: Congural invariance 2289.258 658 0.923 - 0.912 0.060 0.057, 0.062 0.072
M5b: Metric invariance 2322.667 679 0.923 0.000 0.914 0.059 0.056, 0.062 0.074
M6b: Scalar invariance 2384.968 707 0.921 0.002 0.916 0.058 0.056, 0.061 0.074
Notes: a Fit ind ex for measureme nt invariance tests of the mo del across genders
b Fit indices for m easurement invariance te sts of the model across g rades
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Kang et al. BMC Psychology (2025) 13:235
validated the measurement invariance of the AMS across
gender and ability groups among Singaporean second-
ary students [15]. Similarly, Tóth-Király et al. conrmed
the measurement invariance of the AMS across gender
and age groups in Hungarian high school students [79].
In contrast to these previous studies, the present study
focused on a domain-specic adaptation of the AMS tai-
lored to the EFL context. Notably, in addition to estab-
lishing measurement invariance across gender, age, and
ability groups, the present study documented the AMS’s
invariance across grade levels, thereby oering a more
comprehensive validation of the scale.
In addressing the third research question, our ndings
revealed a negative predictive eect of AMO on learn-
ing engagement, perceived teacher support, and EFL
achievement. Conversely, intrinsic and extrinsic moti-
vation (except EM-ER) demonstrated a positive predic-
tive impact on these outcomes. is evidence supports
the between-network validity of the EFL-related AMS.
Our results suggest both intrinsic and extrinsic motiva-
tion (excluding EM-ER) are advantageous for secondary
EFL learners in terms of academic and well-being out-
comes. As EFL learners’ intrinsic and extrinsic motiva-
tion towards English learning strengthens, they are more
likely to receive incredible support from their English
teachers, engage more actively in learning activities, and
achieve higher prociency levels in English. Although the
positive inuence of intrinsic motivation on academic
and well-being outcomes has been widely documented
in previous research [29, 34], the role of extrinsic moti-
vation remains relatively unexplored [80, 81]. Within
the framework of self-determination theory, extrinsic
motivation-external regulation was perceived as the
most controlled form of extrinsic motivation [82], with
self-determination ranking only above amotivation [14].
e validated EFL-related AMS oers a valuable tool for
assessing the academic motivation proles of EFL learn-
ers, both within and beyond the studied region. Further-
more, our conrmation of the seven-factor conguration
of the AMS underscores the importance of analysing
each dimension of academic motivation separately to
gain a more nuanced understanding of learners’ motiva-
tional proles.
Limitations and future directions
is study was the rst to validate the EFL-related AMS
and conrm the seven-factor measurement model of
EFL motivation in a sample of Chinese secondary EFL
learners. While the current study was conducted within
a Chinese EFL context, its ndings hold implications for
other EFL contexts. Specically, it underscores the signif-
icance of validating a translated instrument in a context
distinct from its original development. However, three
limitations need to be addressed. First, this study was
Table 5 Regression results of the seven factors of EFL-related motivation with learning engagement, perceived teacher support, and EFL achievement
Motivation Subscales Learning engagement Perceived teacher support EFL achievement
Unstd. Std. t p R2Unstd. Std. t p R2Unstd. Std. t p R2
B SE βB SE βB SE β
AMO − 0.778 0.050 − 0.601 -15.444 *** 0.364 − 0.707 0.049 − 0.556 -14.398 *** 0.310 -15.187 1.219 − 0.417 -12.458 *** 0.187
IM-TK 0.720 0.030 0.749 24.007 *** 0.562 0.612 0.030 0.649 20.158 *** 0.423 9.796 0.767 0.362 12.768 *** 0.146
IM -TA 0.697 0.029 0.736 24.021 *** 0.545 0.582 0.029 0.625 19.831 *** 0.393 9.795 0.750 0.366 13.056 *** 0.150
IM-ES 0.684 0.027 0.767 25.238 *** 0.590 0.569 0.027 0.653 20.760 *** 0.427 9.538 0.690 0.382 13.826 *** 0.160
EM-ID 0.730 0.045 0.573 16.204 *** 0.335 0.763 0.046 0.609 16.749 *** 0.373 10.773 1.105 0.298 9.749 *** 0.109
EM-IN 0.240 0.030 0.259 7.983 *** 0.086 0.189 0.030 0.208 6.361 *** 0.052 2.950 0.784 0.112 3.762 *** 0.041
EM-ER 0.061 0.025 0.078 2.470 * 0.027 0.075 0.025 0.097 3.027 ** 0.019 0.069 0.647 0.003 0.107 ns 0.030
Notes: Unstd. = U nstandardized coe cients; Std. = Standardize d coecients; SE = St andard error. *** p <.001; * * p <.01; * p <.05; ns = nonsi gnicant
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Page 11 of 13
Kang et al. BMC Psychology (2025) 13:235
conducted in China’s dominant Confucian Heritage Cul-
ture (CHC) region, conrming the applicability of EFL-
related AMS in the CHC context. In addition to CHC,
Chinese culture has other vital components, such as Tao-
ism, Buddhism, and the cultures of 55 ethnic minorities
[83]. us, recruiting participants from broad cultural
settings is recommended to expand the applicability of
EFL-related AMS. Second, potential same-source bias
could not be wholly excluded, for the data in the pres-
ent study were self-reported due to an inherent social
desirability bias [84]. e utilisation of a large sample
with relatively random selection and the corroboration
of research ndings by other studies indicate the reliabil-
ity and applicability of our research results in exploring
Chinese secondary EFL learners’ motivational proles.
Even so, collecting data from multiple sources in future
research may increase the validity of the conclusions [85].
ird, in the between-network validity study, the present
study focused solely on academic engagement, teacher
support, and EFL achievement. Future endeavours could
expand the scope of theoretically pertinent constructs
by exploring the linkages between the seven subtypes of
academic motivation and other outcomes, such as psy-
chological well-being [78], goal orientation and academic
well-being [86], achievement emotions [87], and educa-
tional aspirations [88].
Conclusion
Academic motivation shapes students’ learning experi-
ences and fosters their overall development. By deepening
our understanding of academic motivation and actively
cultivating it, educators and researchers can design more
eective teaching strategies, ultimately improving educa-
tional outcomes and promoting holistic student growth.
However, existing literature lacks consensus regarding
the structure of the AMS. Moreover, most studies vali-
dating the AMS have predominantly focused on West-
ern contexts, often overlooking domain-specic nature
and cultural nuances. In response to this gap, the present
study utilised data from Chinese secondary EFL learn-
ers and employed within-network and between-network
approaches to evaluate the structure and validity of the
AMS within the CHC context. Our ndings support the
seven-factor model of the AMS, arming its applicability
for assessing the motivation proles of Chinese second-
ary EFL learners. In addition, the established measure-
ment invariance of the EFL-related AMS across genders
and grade levels underscores its ecacy for comparative
analyses across these dimensions. is nding further
attests to the scale’s stability, reliability, and extensive
applicability in the EFL education context. Implementing
this validated EFL-related AMS can provide English edu-
cators with a comprehensive understanding of students’
motivation in learning English, thereby informing and
enhancing instructional strategies to better support stu-
dent engagement and motivation.
Abbreviations
AMS Academic motivation scale.
SDT Self-determination theory.
IM-TK Intrinsic motivation-to know.
IM-TA Intrinsic motivation-to accomplish.
IM-ES Intrinsic motivation-to experience stimulation.
EM-ER Extrinsic motivation-external regulation.
EM-IN Extrinsic motivation-introjected regulation.
EM-ID Extrinsic motivation-identied regulation.
Supplementary Information
The online version contains supplementary material available at h t t p s : / / d o i . o r
g / 1 0 . 1 1 8 6 / s 4 0 3 5 9 - 0 2 5 - 0 2 5 7 3 - 8.
Supplementary Material 1
Acknowledgements
For data collection, we would like to extend our gratitude to the
administrative sta at Shiji Jinyuan School Aliated to Yunnan Normal
University for allowing us to contact head teachers and EFL teachers. Great
thanks to Ms. Man Shi for her coordination. We also gratefully thank all the
head teachers and EFL teachers in each class for allowing us to contact their
students. Thanks also to all the student participants for their collaboration in
this project.
Author contributions
X.K. - Conceptualization, Data curation, Formal analysis, Funding acquisition,
Investigation, Methodology, Project administration, Resources, Software,
Visualization, Writing - original draft, Writing - review & editing D. H. - Formal
analysis, Funding acquisition, Methodology, Project administration, Resources,
Software, Writing - original draft, Writing - review & editing, Communication
between the journal and the authors Y. W. - Formal analysis, Methodology,
Software, Writing - original draft, Writing - review & editing J. L. - Methodology,
Writing - review & Editing.
Funding
This study is funded by the 2024 Guangzhou Municipal Education Bureau
Project (No. 2024312376). Additionally, this study is supported by the National
Natural Science Foundation of China (No. 62377042).
Data availability
The corresponding author will provide related information about the data and
materials presented in the article when requested.
Declarations
Ethics approval and consent to participate
Ethical approval for the present study was obtained from the University
of Hong Kong (Human Research Ethics Committee’s Reference Number:
EA2003020). Prior to the commencement of the questionnaire survey, all
participants signed consent forms, verbal informed consent was also obtained
from participants’ parents or legal guardians, and anonymous pen-and-paper
questionnaires were then distributed. The procedure of obtaining consent
is approved by the ethics committee. This study reporting experiments on
humans has conrmed that all experiments were performed in accordance
with relevant guidelines and regulations. For more details about the
ethical principles and guidelines for educational research involving human
participants, please refer to h t t p s : / / w w w . r s s . h k u . h k / i n t e g r i t y / e t h i c s - c o m p l i a n
c e / h r e c.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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Page 12 of 13
Kang et al. BMC Psychology (2025) 13:235
Received: 22 November 2024 / Accepted: 6 March 2025
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